Top Remote Entry Level Data & Analytics Jobs in Pittsburgh, PA

The Data Strategist will manage measurement strategies for marketing campaigns, leveraging data analysis, statistical modeling, and customer insights. Key responsibilities include identifying performance insights, maintaining client relationships, presenting findings, and improving reporting processes.

The Revenue Cycle Representative-ASC at Surgical Notes will manage accounts receivable by following up and collecting on third party payor accounts. Responsibilities include working through aged accounts, reviewing denials, maintaining client communication, and collaborating with the team to ensure timely collections.

Seeking a skilled Data Operations Engineer to support data annotation production processes by optimizing, maintaining, and scaling data labeling workflows using tools like Labelbox. Responsibilities include scripting in Python, identifying bottlenecks, integrating third-party tools, and providing technical support to project managers and labelers.

Oscar is hiring a Senior Manager, Data Science to lead a team of data scientists in leveraging data for enhancing healthcare services. Responsibilities include translating business goals into plans, managing a team, and collaborating with cross-functional teams. The role offers a salary range of $174,400 - $228,900 per year and is based in New York City, Tempe, or Los Angeles with remote options available for residents of specific states.

The consultant will analyze pricing trends and market dynamics, develop strategies to optimize profitability and competitiveness of pharmaceutical products on a global scale, working closely with the company team.

As a Workforce Management Analyst II at Wisetack, you will manage scheduling and efficiency for Customer Support and Loan Servicing teams. Responsibilities include monitoring agent performance, capacity planning, developing schedules, and analyzing key metrics to drive operational improvements.

Join Hims & Hers Analytics and Data Science team to engage in data-driven decision making, improve user experience, and contribute to product development. Collaborate with business leaders, marketers, and product teams to drive analytical insights, and leverage machine learning for innovative solutions across the organization.